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Monkey patching is a technique in programming where existing code is modified at runtime.
Monkey patching involves modifying or extending the behavior of a class or module at runtime.
It is often used in testing or debugging scenarios to temporarily change the behavior of a piece of code.
Monkey patching can be done in languages like Python by directly modifying the class or module, or using libraries like 'mock'.
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MapReduce is a programming model used in Hadoop for processing large datasets in parallel.
MapReduce breaks down a big data processing task into smaller chunks that can be processed in parallel.
The 'map' phase processes input data and produces key-value pairs.
The 'reduce' phase aggregates the key-value pairs generated by the map phase.
MapReduce is fault-tolerant and scalable, making it ideal for processing large dataset...
Multithreading can be used to process large files efficiently by dividing the work among multiple threads.
Divide the file into smaller chunks and assign each chunk to a separate thread for processing.
Use synchronization techniques to ensure data integrity and avoid race conditions.
Consider using a thread pool to manage the creation and execution of threads efficiently.
Example: Reading a large CSV file and processing ea
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